A hybrid stochastic method with adaptive time step control for reaction–diffusion systems
Related Research Unit(s)
|Journal / Publication||Journal of Computational Physics|
|Online published||12 Dec 2018|
|Publication status||Published - 15 Feb 2019|
|Link to Scopus||https://www.scopus.com/record/display.uri?eid=2-s2.0-85058962507&origin=recordpage|
Randomness often plays an important role in the spatial and temporal dynamics of biological systems. General stochastic simulation methods may lead to excessive computational cost for a system in which a large number of molecules involved. Therefore, multi-scale hybrid simulation methods become important for stochastic simulations. Here we build a spatially hybrid method which couples two approaches: discrete stochastic simulation and continuous stochastic differential equations. In our method, the locations of the interfaces between the two approaches are changing according to the distribution of molecules in a one-dimensional domain. To balance the accuracy and efficiency, the time step of the numerical method for the continuous stochastic differential equations is adapted to the dynamics of the molecules near the adaptive interfaces. The simulation results for a linear system and two nonlinear biological systems in different one-dimensional domains demonstrate the effectiveness and advantage of our new hybrid method with the adaptive time step control.
- Biological patterning, Hybrid method, Reaction–diffusion systems, Stochastic simulation
Journal of Computational Physics, Vol. 379, 15.02.2019, p. 392-402.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal
Lo, W-C & Mao, S 2019, 'A hybrid stochastic method with adaptive time step control for reaction–diffusion systems', Journal of Computational Physics, vol. 379, pp. 392-402. https://doi.org/10.1016/j.jcp.2018.11.042